Abstract
The higher energy and luminosity from the LHC in Run 2 have put increased pressure on CMS computing resources. Extrapolating to even higher luminosities (and thus higher event complexities and trigger rates) beyond Run 3, it becomes clear that simply scaling up the the current model of CMS computing alone will become economically unfeasible. High Performance Computing (HPC) facilities, widely used in scientific computing outside of HEP, have the potential to help fill the gap. Here we describe the U.S.CMS efforts to integrate US HPC resources into CMS Computing via the HEPCloud project at Fermilab. We present advancements in our ability to use NERSC resources at scale and efforts to integrate other HPC sites as well. We present experience in the elastic use of HPC resources, quickly scaling up use when so required by CMS workflows. We also present performance studies of the CMS multi-threaded framework on both Haswell and KNL HPC resources.
Highlights
The LHC experiments have their own computing infrastructures which have been successfully used during Run 1 and Run 2 of LHC
Why are we looking at using High Performance Computing (HPC) sites to complement our own resources now? The reason is resource extrapolations for the planned LHC upgrade to the HL-LHC
NERSC is a HPC user facility operated by Lawrence Berkeley National Laboratory for the United States Department of Energy (DOE) Office of Science
Summary
The LHC experiments have their own computing infrastructures which have been successfully used during Run 1 and Run 2 of LHC. The reason is resource extrapolations for the planned LHC upgrade to the HL-LHC. These increases result in more CMS collission events collected and these events have a higher internal complexity, making them harder to reconstruct. Will we have more events to process, the processing time per event will go up. All of this leads to a very large increase in resource demands for HL-LHC, as shown in figure 2
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